1.
Introduction
Three Diﬀerent MBAC Algorithms
Practical Implementations of CAC
Conclusions
Measurement-Based Admission Control Algorithms
Bob Callaway Joni Finlon Susan Stewart
North Carolina State University
CSC/ECE 776 - Performance Evaluation of Computer Networks
Student Research Presentation
April 27, 2004
Bob Callaway, Joni Finlon, Susan Stewart Measurement-Based Admission Control Algorithms
2.
Introduction
Three Diﬀerent MBAC Algorithms
Practical Implementations of CAC
Conclusions
Presentation Outline
1 Introduction
Goals of Connection Admission Control
Types of CAC Algorithms
Eﬀective Bandwidth
Overview of Measurement-Based Admission Control
2 Three Diﬀerent MBAC Algorithms
CLR Upperbound Formula
Decision-Theoretic Approach
MBAC with Aggregate Traﬃc Envelopes
Comparison of Algorithm Characteristics
3 Practical Implementations of CAC
Voice Over IP (VoIP)
Video Conferencing
Multimedia Resource Control
4 Conclusions
Bob Callaway, Joni Finlon, Susan Stewart Measurement-Based Admission Control Algorithms
3.
Introduction Goals of Connection Admission Control
Three Diﬀerent MBAC Algorithms Types of CAC Algorithms
Practical Implementations of CAC Eﬀective Bandwidth
Conclusions Overview of Measurement-Based Admission Control
Section Outline
1 Introduction
Goals of Connection Admission Control
Types of CAC Algorithms
Eﬀective Bandwidth
Overview of Measurement-Based Admission Control
2 Three Diﬀerent MBAC Algorithms
CLR Upperbound Formula
Decision-Theoretic Approach
MBAC with Aggregate Traﬃc Envelopes
Comparison of Algorithm Characteristics
3 Practical Implementations of CAC
Voice Over IP (VoIP)
Video Conferencing
Multimedia Resource Control
4 Conclusions
Bob Callaway, Joni Finlon, Susan Stewart Measurement-Based Admission Control Algorithms
4.
Introduction Goals of Connection Admission Control
Three Diﬀerent MBAC Algorithms Types of CAC Algorithms
Practical Implementations of CAC Eﬀective Bandwidth
Conclusions Overview of Measurement-Based Admission Control
Congestion Control
The Role of Congestion Control
−→ To protect the network and the user in order to achieve
network performance objectives and optimize the usage of network
resources
Congestion control can be either preventive or reactive
Connection admission control is a preventive congestion
control method
Bob Callaway, Joni Finlon, Susan Stewart Measurement-Based Admission Control Algorithms
5.
Introduction Goals of Connection Admission Control
Three Diﬀerent MBAC Algorithms Types of CAC Algorithms
Practical Implementations of CAC Eﬀective Bandwidth
Conclusions Overview of Measurement-Based Admission Control
Goals of Connection Admission Control
Three Main Goals of Connection Admission Control
Protect the network by preventing congestion
Meet QoS requirements of all connections
Obtain maximum statistical multiplexing gain
Uses an algorithm to decide whether to accept or reject a
request for a new connection to the network
Connection acceptance is based on two questions:
Does the new connection aﬀect the QoS currently being
carried by the switch?
Can the switch provide the QoS requested by the new
connection?
Bob Callaway, Joni Finlon, Susan Stewart Measurement-Based Admission Control Algorithms
6.
Introduction Goals of Connection Admission Control
Three Diﬀerent MBAC Algorithms Types of CAC Algorithms
Practical Implementations of CAC Eﬀective Bandwidth
Conclusions Overview of Measurement-Based Admission Control
Nonstatistical Connection Admission Control
Also called deterministic allocation or peak bandwidth
allocation
Requires that the peak rate of the connection be reserved for
a particular source
Advantages Disadvantages
It is easy to make a The network will be
decision about whether underutilized most of the
to accept or reject a new time (unless users are
connection transmitting CBR traﬃc)
Bob Callaway, Joni Finlon, Susan Stewart Measurement-Based Admission Control Algorithms
7.
Introduction Goals of Connection Admission Control
Three Diﬀerent MBAC Algorithms Types of CAC Algorithms
Practical Implementations of CAC Eﬀective Bandwidth
Conclusions Overview of Measurement-Based Admission Control
Statistical Connection Admission Control
Allocated bandwidth is less than the peak rate of a source
Advantages Disadvantages
Network resources will be More diﬃcult to implement
better utilized Can be CPU intensive
x 10 Plot of Traffic Trace vs. Estimated Effective Bandwidths − Meter Implementation: 1 Stream
5
5
Actual Traffic
Gaussian Method
4.5 Courcoubetis Method
Norros Method
4
3.5
Throughput (bytes/sec)
3
2.5
2
1.5
1
0.5
0
0 100 200 300 400 500 600 700 800 900 1000
Time (sec)
Bob Callaway, Joni Finlon, Susan Stewart Measurement-Based Admission Control Algorithms
8.
Introduction Goals of Connection Admission Control
Three Diﬀerent MBAC Algorithms Types of CAC Algorithms
Practical Implementations of CAC Eﬀective Bandwidth
Conclusions Overview of Measurement-Based Admission Control
Motivation of Eﬀective Bandwidth
How do we determine the number of connections to admit to the
network to maximize eﬃciency by using statistical multiplexing?
Eﬀective Bandwidth!
Eﬀective bandwidth estimates the amount of bandwidth that
should be allocated to a class of network traﬃc in order to
meet a QoS requirement, such as a delay or loss constraint
1
C= log E e θX [0,t]
θt
Bob Callaway, Joni Finlon, Susan Stewart Measurement-Based Admission Control Algorithms
9.
Introduction Goals of Connection Admission Control
Three Diﬀerent MBAC Algorithms Types of CAC Algorithms
Practical Implementations of CAC Eﬀective Bandwidth
Conclusions Overview of Measurement-Based Admission Control
Measurement-Based Admission Control: An Overview
Why use a measurement-based scheme?
Non-measurement-based methods use the worst case bounds
and result in low utilization of the network
Zero (or a very small number of) a priori assumptions must be
made about the arrival process of the traﬃc, since
measurements are used to describe the traﬃc
Useful for services that do not require tight guarantees, rather
more relaxed service commitments
Results in high network utilization and an acceptable level of
service
Bob Callaway, Joni Finlon, Susan Stewart Measurement-Based Admission Control Algorithms
10.
Introduction CLR Upperbound Formula
Three Diﬀerent MBAC Algorithms Decision-Theoretic Approach
Practical Implementations of CAC MBAC with Aggregate Traﬃc Envelopes
Conclusions Comparison of Algorithm Characteristics
Section Outline
1 Introduction
Goals of Connection Admission Control
Types of CAC Algorithms
Eﬀective Bandwidth
Overview of Measurement-Based Admission Control
2 Three Diﬀerent MBAC Algorithms
CLR Upperbound Formula
Decision-Theoretic Approach
MBAC with Aggregate Traﬃc Envelopes
Comparison of Algorithm Characteristics
3 Practical Implementations of CAC
Voice Over IP (VoIP)
Video Conferencing
Multimedia Resource Control
4 Conclusions
Bob Callaway, Joni Finlon, Susan Stewart Measurement-Based Admission Control Algorithms
11.
Introduction CLR Upperbound Formula
Three Diﬀerent MBAC Algorithms Decision-Theoretic Approach
Practical Implementations of CAC MBAC with Aggregate Traﬃc Envelopes
Conclusions Comparison of Algorithm Characteristics
Rate Envelope Multiplexing vs. Rate Sharing Multiplexing
Rate Envelope Multiplexing (REM)
Buﬀering eﬀect is not taken into account when evaluating
cell-level performance
Queueing process at the output port buﬀer is not considered
Provides for faster computations
Rate Sharing Multiplexing (RSM)
Requires model for queueing process at output port buﬀer
Can achieve higher eﬃciency than REM methods
Computationally complex; also dependent on input traﬃc
model
Bob Callaway, Joni Finlon, Susan Stewart Measurement-Based Admission Control Algorithms
12.
Introduction CLR Upperbound Formula
Three Diﬀerent MBAC Algorithms Decision-Theoretic Approach
Practical Implementations of CAC MBAC with Aggregate Traﬃc Envelopes
Conclusions Comparison of Algorithm Characteristics
Dynamic CAC in ATM Networks
∞ +
k − Cs
L p (·; t) θn+1 (k)
ˆ
L
ˆ k=0
B=
ˆ(t) + san+1
a
Algorithm Overview
Independent of the classiﬁcation of calls and does not use a
model for the arrival process
Makes admission decision by comparing measured upper
bound of loss probability against QoS standard
Uses measurements to estimate the pdf of the number of
arriving cells per call in a renewal period
Bob Callaway, Joni Finlon, Susan Stewart Measurement-Based Admission Control Algorithms
13.
Introduction CLR Upperbound Formula
Three Diﬀerent MBAC Algorithms Decision-Theoretic Approach
Practical Implementations of CAC MBAC with Aggregate Traﬃc Envelopes
Conclusions Comparison of Algorithm Characteristics
Dynamic CAC in ATM Networks (continued)
Algorithm Details
Uses exponential weighting to increase/decrease importance
of measurements/signalled parameters
If a new call request is received within the renewal period, the
pdf is shifted by convolution to take the new worst-case cell
arrival distribution into consideration
Bob Callaway, Joni Finlon, Susan Stewart Measurement-Based Admission Control Algorithms
14.
Introduction CLR Upperbound Formula
Three Diﬀerent MBAC Algorithms Decision-Theoretic Approach
Practical Implementations of CAC MBAC with Aggregate Traﬃc Envelopes
Conclusions Comparison of Algorithm Characteristics
A Decision-Theoretic Approach to CAC in ATM Networks
Algorithm Overview
Key aspect of algorithm is
time scale decomposition
Bayesian decision-theoretic
framework parameterizes the
tradeoﬀ between the costs
and beneﬁts of accepting an
additional call into the
network
Uses a measure of burstiness
(peak to mean ratio) in
calculations
Bob Callaway, Joni Finlon, Susan Stewart Measurement-Based Admission Control Algorithms
15.
Introduction CLR Upperbound Formula
Three Diﬀerent MBAC Algorithms Decision-Theoretic Approach
Practical Implementations of CAC MBAC with Aggregate Traﬃc Envelopes
Conclusions Comparison of Algorithm Characteristics
A Decision-Theoretic Approach to CAC in ATM Networks
Algorithm Details
Makes the admission control
decision by comparing the
instantaneous load to a given
threshold
Uses the control parameter y to
represent the tradeoﬀ between
utilization and cell loss
Cell loss ratio is eﬀected by rate of
change of the parameter p.
s= [U(p, λ) − (y − 1)M(p, λ)] f (p, λ)dpdλ
Bob Callaway, Joni Finlon, Susan Stewart Measurement-Based Admission Control Algorithms
16.
Introduction CLR Upperbound Formula
Three Diﬀerent MBAC Algorithms Decision-Theoretic Approach
Practical Implementations of CAC MBAC with Aggregate Traﬃc Envelopes
Conclusions Comparison of Algorithm Characteristics
MBAC with Aggregate Traﬃc Envelopes
Algorithm Overview
Measures the maximal rate
envelope of the aggregate traﬃc,
since the extreme values of the
aggregate ﬂow are likely to lead to
losses
Takes measurements in slotted
time, and computes statistics of
the envelope over M time scales s
1 1
Rk = max au
Can make admission decision with kτ t−T +k≤s≤t
u=s−k+1
regards to a speciﬁed loss rate
and/or a given delay bound
Bob Callaway, Joni Finlon, Susan Stewart Measurement-Based Admission Control Algorithms
17.
Introduction CLR Upperbound Formula
Three Diﬀerent MBAC Algorithms Decision-Theoretic Approach
Practical Implementations of CAC MBAC with Aggregate Traﬃc Envelopes
Conclusions Comparison of Algorithm Characteristics
MBAC with Aggregate Traﬃc Envelopes
Algorithm Details
A conﬁdence level is derived such that for a given α, the
traﬃc will not exceed the maximal envelope
The admission control decision is made by testing the new
aggregate envelope against the delay/loss criterion
In the worst case, this algorithm bounds the loss probability or
the maximum delay; in the best case, signiﬁcant statistical
multiplexing gains can be realized
max ¯
kτ (Rk + rk + ασk − C ) ≤ Cd
k=1,2,...,T
¯
RT + rT + ασT ≤ C
Bob Callaway, Joni Finlon, Susan Stewart Measurement-Based Admission Control Algorithms
18.
Introduction CLR Upperbound Formula
Three Diﬀerent MBAC Algorithms Decision-Theoretic Approach
Practical Implementations of CAC MBAC with Aggregate Traﬃc Envelopes
Conclusions Comparison of Algorithm Characteristics
Comparison of Algorithm Characteristics
Method Measurement Decision Memory Model Assumed
SS91 O(M) O(M) O(M) None
GKK95 O(1) O(1) O(N) Poisson/Exponential
QK01 O(T) O(1) O(T) None
M = Number of Bins in Distribution N = Number of Connections T = Number of Time Slots
Comparisons
REM models are less dependent on a priori traﬃc assumptions
SS91 does not make any traﬃc assumptions, but it has the
highest computational costs
QK01 has been shown to be practically implementable in
testbed experiments using RSVP
Bob Callaway, Joni Finlon, Susan Stewart Measurement-Based Admission Control Algorithms
19.
Introduction
Voice Over IP (VoIP)
Three Diﬀerent MBAC Algorithms
Video Conferencing
Practical Implementations of CAC
Multimedia Resource Control
Conclusions
Section Outline
1 Introduction
Goals of Connection Admission Control
Types of CAC Algorithms
Eﬀective Bandwidth
Overview of Measurement-Based Admission Control
2 Three Diﬀerent MBAC Algorithms
CLR Upperbound Formula
Decision-Theoretic Approach
MBAC with Aggregate Traﬃc Envelopes
Comparison of Algorithm Characteristics
3 Practical Implementations of CAC
Voice Over IP (VoIP)
Video Conferencing
Multimedia Resource Control
4 Conclusions
Bob Callaway, Joni Finlon, Susan Stewart Measurement-Based Admission Control Algorithms
20.
Introduction
Voice Over IP (VoIP)
Three Diﬀerent MBAC Algorithms
Video Conferencing
Practical Implementations of CAC
Multimedia Resource Control
Conclusions
Example of CAC: Voice Over IP (VoIP)
Bob Callaway, Joni Finlon, Susan Stewart Measurement-Based Admission Control Algorithms
21.
Introduction
Voice Over IP (VoIP)
Three Diﬀerent MBAC Algorithms
Video Conferencing
Practical Implementations of CAC
Multimedia Resource Control
Conclusions
Example of MBAC: Voice Over IP (VoIP)
VoIP Examples
Cisco
IOS Software
Gateways
Bob Callaway, Joni Finlon, Susan Stewart Measurement-Based Admission Control Algorithms
22.
Introduction
Voice Over IP (VoIP)
Three Diﬀerent MBAC Algorithms
Video Conferencing
Practical Implementations of CAC
Multimedia Resource Control
Conclusions
Example of CAC: Voice Over IP (VoIP)
Cisco
Bob Callaway, Joni Finlon, Susan Stewart Measurement-Based Admission Control Algorithms
23.
Introduction
Voice Over IP (VoIP)
Three Diﬀerent MBAC Algorithms
Video Conferencing
Practical Implementations of CAC
Multimedia Resource Control
Conclusions
Example of CAC: Voice Over IP (VoIP)
VoIP Examples
NexTone
Multiprotocol Session Controller (MSC)
Bob Callaway, Joni Finlon, Susan Stewart Measurement-Based Admission Control Algorithms
24.
Introduction
Voice Over IP (VoIP)
Three Diﬀerent MBAC Algorithms
Video Conferencing
Practical Implementations of CAC
Multimedia Resource Control
Conclusions
Example of CAC: Video Conferencing
Video Conferencing Examples
Polycom
PathNavigator TM Premier Call
Processing Server Solution
Cisco
Multimedia Conference Manager
H.323 Gatekeeper
Bob Callaway, Joni Finlon, Susan Stewart Measurement-Based Admission Control Algorithms
25.
Introduction
Voice Over IP (VoIP)
Three Diﬀerent MBAC Algorithms
Video Conferencing
Practical Implementations of CAC
Multimedia Resource Control
Conclusions
Example of CAC: Multimedia Resource Control
Alcatel 5430 Session Resource Broker
Bob Callaway, Joni Finlon, Susan Stewart Measurement-Based Admission Control Algorithms
26.
Introduction
Three Diﬀerent MBAC Algorithms
References
Practical Implementations of CAC
Conclusions
Section Outline
1 Introduction
Goals of Connection Admission Control
Types of CAC Algorithms
Eﬀective Bandwidth
Overview of Measurement-Based Admission Control
2 Three Diﬀerent MBAC Algorithms
CLR Upperbound Formula
Decision-Theoretic Approach
MBAC with Aggregate Traﬃc Envelopes
Comparison of Algorithm Characteristics
3 Practical Implementations of CAC
Voice Over IP (VoIP)
Video Conferencing
Multimedia Resource Control
4 Conclusions
Bob Callaway, Joni Finlon, Susan Stewart Measurement-Based Admission Control Algorithms
27.
Introduction
Three Diﬀerent MBAC Algorithms
References
Practical Implementations of CAC
Conclusions
Conclusions
Connection Admission Control
Some type of CAC is needed to ensure the QoS of existing
connections and to control additional connections to the
network
Measurement-based Admission Control Algorithms
How well does it ensure that the service commitments are
upheld?
How high can network utilization reach while still upholding
QoS commitments?
Do the beneﬁts of statistical multiplexing outweigh the cost of
online measurements and other statistical computations?
Bob Callaway, Joni Finlon, Susan Stewart Measurement-Based Admission Control Algorithms
28.
Introduction
Three Diﬀerent MBAC Algorithms
References
Practical Implementations of CAC
Conclusions
H. Saito, K. Shiomoto.
Dynamic Call Admission Control in ATM Networks.
IEEE Journal on Selected Areas in Communications, 1991.
R. Gibbens, F. Kelly, P. Key.
A Decision-Theoretic Approach to Call Admission Control in
ATM Networks.
IEEE Journal on Selected Areas in Communications, 1995.
J. Qiu, E. Knightly.
Measurement-Based Admission Control with Aggregate Traﬃc
Envelopes.
IEEE/ACM Transactions on Networking, April 2001.
H. Perros, K. Elsayed
Call Admission Control Schemes: A Review.
IEEE Communications Magazine, November 1996.
Bob Callaway, Joni Finlon, Susan Stewart Measurement-Based Admission Control Algorithms
29.
Introduction
Three Diﬀerent MBAC Algorithms
References
Practical Implementations of CAC
Conclusions
K. Shiomoto, N. Yamanaka, T. Takahashi.
Overview of Measurement-Based Connection Admission
Control Methods in ATM Networks.
IEEE Communication Surveys, First Quarter 1999.
E. Knightly, N. Shroﬀ.
Admission Control for Statistical QoS: Theory and Practice.
IEEE Network, March/April 1999.
S. Jamin, P.B. Danzig, S.J. Shenker, L. Zhang
A Measurement-based Admission Control Algorithm for
Integrated Services Packet Networks (Extended Version)
IEEE/ACM Transactions on Networking, February 1997
S. Jamin, P.B. Danzig, S.J. Shenker
Comparison of Measurement-based Admission Control
Algorithms for Controlled-Load Service
IEEE INFOCOM, 1997
Bob Callaway, Joni Finlon, Susan Stewart Measurement-Based Admission Control Algorithms
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